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| BILB3013 | Applied matrix theory | 4+0+0 | ECTS:4 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Elective | | Department | COMPUTER SCIENCE | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 4 hours of lectures per week | | Lecturer | Doç. Dr. Melek ERİŞ BÜYÜKKAYA | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | To learn advanced methods of linear algebra and matrix theory, which are applied in many scientific fields today, with the help of MATLAB. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | Can perform matrix operations on the computer | 1,4 | 3,4, | | LO - 2 : | Elimination with matrices on the computer, matrix inversion can be done with the Gauss-Jordan method | 1,4 | 3,4, | | LO - 3 : | Can find the solution of the matrix equation Ax=b on the computer | 1,4 | 3,4, | | LO - 4 : | Find Eigenvalues ??and Eigenvectors and diagonalize the matrix on the computer | 1,4 | 3,4, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| ntroduction to MATLAB, workspace structure, Variables, vectors and matrices, MATLAB scripts, Operations, Basic graph drawing, Visualization, Programming, Function structures, Matrices and linear equations, Gauss elimination, Elimination with matrices, Gauss-Jordan method Matrix inversion with, Factorization, LU decomposition, Transpose and Permutation matrices, Vector space and its subspaces, Null space, Row, column and left null space, Rank, Solution of Ax=b, Linear independence, Base and dimension, Orthogonality, Projections, Least squares approach, Orthogonal bases and Gram-Schimidt, Determinants, Cofactors, Cramer's rule, Eigenvalues ??and Special vectors, Diagonalization of matrices, Symmetric, Positive definite and similar matrices, Complex vectors and matrices, Hermitian and Unitary matrices, MATLAB Applications. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction to MATLAB, workspace structure. | | | Week 2 | Variables, vectors and matrices in MATLAB. | | | Week 3 | Basic graphic drawing, visualization, programming, function structures in MATLAB. | | | Week 4 | Matrices, Linear equations, Gauss elimination, MATLAB applications. | | | Week 5 | Elimination with matrices, matrix inversion with Gauss-Jordan method and MATLAB applications | | | Week 6 | Factorization, LU decomposition, Transpose, Permutation matrices and MATLAB applications | | | Week 7 | Vector space, Subvector spaces, Null space, Row, column and left null space, Rank and MATLAB applications | | | Week 8 | Solution of matrix equation Ax=b, Least squares approach and MATLAB applications | | | Week 9 | exam | | | Week 10 | Linear independence, Base and dimension, Orthogonality, Projections, Orthogonal bases and Gram-Schimidt, MATLAB applications | | | Week 11 | Determinants, Cofactors, Cramer's rule and MATLAB applications | | | Week 12 | Eigenvalues ??and Eigenvectors, Diagonalization of Matrices and MATLAB applications | | | Week 13 | Symmetric, Positive definite and similar matrices, MATLAB applications | | | Week 14 | Complex vectors and matrices, Hermitian and Unitary matrices, MATLAB applications | | | Week 15 | Project Presentations | | | Week 16 | Exam | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Project | 15 | | 1,5s | 50 | | End-of-term exam | 16 | | 1,5s | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Proje | 1 | 1 | 1 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 2 |
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